{"id":"W6926677808","doi":"10.25384/sage.22677947","title":"sj-docx-2-smx-10.1177_00811750231163832 – Supplemental material for Evaluation of Respondent-Driven Sampling Prevalence Estimators Using Real-World Reported Network Degree","year":2023,"lang":"en","type":"article","venue":"Sage Journals Data","topic":"Microbial Natural Products and Biosynthesis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; University Health Network","funders":"","keywords":"Estimator; Degree (music); Sampling (signal processing); Estimation; Sampling design; Sample (material)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.009095225,0.0009263213,0.0008315468,0.003669328,0.0009808877,0.002824558,0.002664026,0.001219906,0.8070185],"category_scores_gemma":[0.1238669,0.0009153058,0.0009141415,0.005445457,0.0005208428,0.002231407,0.001719251,0.001731822,0.3704458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001646271,"about_ca_system_score_gemma":0.003102483,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0147559,"about_ca_topic_score_gemma":0.02191493,"domain_scores_codex":[0.9958444,0.001089714,0.0004874958,0.0005185314,0.001795375,0.0002644919],"domain_scores_gemma":[0.8685135,0.09304119,0.003259675,0.0102591,0.02286611,0.002060444],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007777931,0.0000633771,0.001179705,0.0003026795,0.00002057029,0.000009452598,0.00006464189,0.0003590021,0.00007431323,0.0009402959,0.9893631,0.007545111],"study_design_scores_gemma":[0.001574802,0.0003275541,0.03376162,0.001278548,0.000132557,0.0001568343,0.001543172,0.007598425,0.00227405,0.01269838,0.9384925,0.0001617603],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001067491,0.00002275956,0.00401352,0.0004600641,0.0002328171,0.0004430391,0.9768983,0.003976014,0.01288605],"genre_scores_gemma":[0.02379552,0.0001411575,0.02620999,0.001374606,0.000346062,0.005512048,0.8673936,0.01074187,0.06448518],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9909047,"threshold_uncertainty_score":0.2752647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2694589866667901,"score_gpt":0.4340250103334323,"score_spread":0.1645660236666421,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}